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As a follow-up to the most recent seriesofposts, you may enjoy this TED talk by David Epstein. Epstein is the author of The Sports Geneand offered the claim that kicked off those earlier posts–that he could accurately guess an Olympian’s sport knowing only her height and weight.

The talk offers some additional context for Epstein’s claim. Specifically Epstein describes how the average height and weight in a set of 24 sports has become more different over time:

In the early half of the 20th century,physical education instructors and coacheshad the idea that the average body type was the best for all athletic endeavors:medium height, medium weight, no matter the sport.And this showed in athletes’ bodies.In the 1920s, the average elite high-jumperand average elite shot-putter were the same exact size.But as that idea started to fade away,as sports scientists and coaches realized that rather than the average body type,you want highly specialized bodiesthat fit into certain athletic niches,a form of artificial selection took place,a self-sorting for bodies that fit certain sports,and athletes’ bodies became more different from one another.Today, rather than the same size as the average elite high jumper,the average elite shot-putteris two and a half inches tallerand 130 pounds heavier.And this happened throughout the sports world.

Here’s the chart used to support that point, with data points from the early twentieth century in yellow and more recent data points in blue:

Average height and mass for athletes in 24 sports in the early twentieth century (yellow) and today (blue)

This suggests that it has become easier over time to guess individuals’ sports based on physical characteristics, but as we saw it is still difficult to do with a high degree of accuracy.

Another interesting change highlighted in the talk is the role of technology:

In 1936, Jesse Owensheld the world record in the 100 meters.Had Jesse Owens been racing last yearin the world championships of the 100 meters,when Jamaican sprinter Usain Bolt finished,Owens would have still had 14 feet to go…. [C]onsider that Usain Bolt started by propelling himself out of blocksdown a specially fabricated carpetdesigned to allow him to travelas fast as humanly possible.Jesse Owens, on the other hand,ran on cinders, the ash from burnt wood,and that soft surface stole far more energyfrom his legs as he ran.Rather than blocks, Jesse Owens had a gardening trowelthat he had to use to dig holes in the cinders to start from.Biomechanical analysis of the speedof Owens’ joints shows that had been runningon the same surface as Bolt,he wouldn’t have been 14 feet behind,he would have been within one stride.

The third change Epstein discusses is more dubious: a “changing mindset” among athletes giving them a “can do” attitude. In particular he mentions Roger Bannister’s four-minute mile as a major psychological breakthrough in sporting. As this interview makes clear, Bannister attributes the fact that no progress was made in the fastest mile time between 1945 and 1954 to the destruction, rationing, and overall quite distracting events of WWII. It’s possible that a four-minute mile was run as early as 1770. I wonder what Epstein’s claims would look like on that time scale?

You have a regular meeting in your calendar. It’s with just one other person. Sometimes you have things to talk to them about and sometimes you don’t. But as long as your calendar says you both have to go, you will both go.

The day of the meeting comes round. There are lots of things that need to be done that day. You look at that meeting sitting obstinately in your calendar and think how useful it would be to get that time back.

Inspiration strikes: why not cancel the meeting? A couple of mouse clicks, an automatic notification sent out, a joyously blank calendar. It seems so easy.

But you can’t bring yourself to do it, to cancel a meeting at such short notice. It would make you look disorganised, unprepared. And what about the other person?

More at the link.

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This holiday season I enjoyed giving, receiving, and playing several new card and board games with friends and family. These included classics such as cribbage, strategy games like Dominion and Power Grid, and the whimsical Munchkin.

Can video and board games teach us more than just strategy? What if games could teach us not to be better thinkers, but just to be… better? A while ago we discussed how monopoly was originally designed as a learning experience to promote cooperation. Lately I have learned of two other such games in a growing genre and wanted to share them here.

Depression Quest is an interactive fiction game where you play as someone living with depression. You are given a series of everyday life events and have to attempt to manage your illness, relationships, job, and possible treatment. This game aims to show other sufferers of depression that they are not alone in their feelings, and to illustrate to people who may not understand the illness the depths of what it can do to people.

In the game, the players read typewritten instructions. The game board is a set of train tracks with box cars, sitting on top of a window pane with broken glass. There are little yellow pegs that represent people, and the player’s job is to efficiently load those people onto the trains. A typewriter sits on one side of the board.

The game takes anywhere from a minute to two hours to play, depending on when the players make a very important discovery. At some point, they turn over a card that has a destination for the train. It says Auschwitz. At that point, for anyone who knows their history, it dawns on the player that they have been loading Jews onto box cars so they can be shipped to a World War II concentration camp and be killed in the gas showers or burned in the ovens.

The key emotion that Romero said she wanted the player to feel was “complicity.”

“People blindly follow rules,” she said. “Will they blindly follow rules that come out of a Nazi typewriter?”

I have tried creating my own board games in the past, and this gives me renewed interest and a higher standard. What is the most thought-provoking moment you have experienced playing games?

If you are getting ready to travel next week, you might want to have a couple of good talks/podcasts handy for the trip. Here are two that I enjoyed, on the topic of government and technology.

The first is about how technology can help governments. Ben Orenstein of “Giant Robots Smashing Into Other Giant Robots” discussesCode for America with Catherine Bracy. Catherine recounts some ups and downs of CfA’s partnerships with cities throughout America and internationally. CfA fellows commit a year to help local governments with challenges amenable to technology. One great example that the podcast discusses is a tool for parents in Boston to see which schools they could send their kids to when the city switched from location-based school assignment to allowing students to attend schools throughout the city. (Incidentally, the school matching algorithm that Boston used was designed by some professors in economics at Duke, who drew on work for which Roth and Shapley won the Nobel Prize.)

The second talk offers another point of view on techno-politics: when government abuses technology. Steve Klabnik‘s “No Secrets Allowed” talk from Golden Gate Ruby Conference discusses recent revelations regarding the NSA and privacy. In particular he explains why “I have nothing to hide” is not an appropriate response. The talk is not entirely hopeless, and includes recommendations such as using Tor. The Ruby Rogues also had a roundtable discussing Klabnik’s presentation, which you can find here.

It seems that the people who actively look for the “best” parking place inevitably spend more total time getting to the store than those people who simply grab the first spot they see…

They observed two distinct strategies: “cycling” and “pick a row, closest space.” They compared the results. “What was interesting,” [Professor Andrew Velkey found], “was although the individual cycling were spending more time driving looking for a parking space, on average they were no closer to the door, time-wise or distance-wise, than people using ‘pick a row, closest space.’”

The best way that I have found to operationalize “pick a row, closest space” is to go a few rows out from the row nearest the store entrance(s). It is important to be driving down the row facing away from the store, so that the first spot you reach is the closest.

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I have long wanted to do a project on reputation in hacker culture. As I have delved into this further (and I still enjoy reading about it), it turns out Eric Raymondsaid it better than I could, nearly 20 years ago:

Like most cultures without a money economy, hackerdom runs on reputation. You’re trying to solve interesting problems, but how interesting they are, and whether your solutions are really good, is something that only your technical peers or superiors are normally equipped to judge.

Accordingly, when you play the hacker game, you learn to keep score primarily by what other hackers think of your skill (this is why you aren’t really a hacker until other hackers consistently call you one). This fact is obscured by the image of hacking as solitary work; also by a hacker-cultural taboo (now gradually decaying but still potent) against admitting that ego or external validation are involved in one’s motivation at all.

Specifically, hackerdom is what anthropologists call a gift culture. You gain status and reputation in it not by dominating other people, nor by being beautiful, nor by having things other people want, but rather by giving things away. Specifically, by giving away your time, your creativity, and the results of your skill.

The traveling salesman problem is simple in its setup but remarkably complicated to solve. You need to visit a number of cities, say 10, and want to find the shortest route that visits all of them exactly once and brings you back to where you started. From a list of routes it is easy to find the shortest one, but it is incredibly hard to verify that it is the shortest of all possible routes.

Finding a solution gets even more difficult when you go from a (mathematically) feasible solution to one that can be implemented in the real world. That is because you have to incorporate a notoriously unreliable component into your plans: human beings.

[I]n trying to apply this mathematics to the real world of deliveries and drivers, UPS managers needed to learn that transportation is as much about people and the unique constraints they impose, as it is about negotiating intersections and time zones….

For one thing, humans are irrational and prone to habit. When those habits are interrupted, interesting things happen. After the collapse of the I-35 bridge in Minnesota, for example, the number of travelers crossing the river, not surprisingly, dropped; but even after the bridge was restored, researcher David Levinson has noted, traffic levels never got near their previous levels again. Habits can be particularly troublesome for planning fixed travel routes for people, like public buses, as noted in a paper titled, “You Can Lead Travelers to the Bus Stop, But You Can’t Make Them Ride,” by Akshay Vij and Joan Walker of the University of California. “Traditional travel demand models assume that individuals are aware of the full range of alternatives at their disposal,” the paper reads, “and that a conscious choice is made based on a tradeoff between perceived costs and benefits.” But that is not necessarily so.

People are also emotional, and it turns out an unhappy truck driver can be trouble. Modern routing models incorporate whether a truck driver is happy or not—something he may not know about himself. For example, one major trucking company that declined to be named does “predictive analysis” on when drivers are at greater risk of being involved in a crash. Not only does the company have information on how the truck is being driven—speeding, hard-braking events, rapid lane changes—but on the life of the driver….

In other words, the traveling salesman problem grows considerably more complex when you actually have to think about the happiness of the salesman.

That’s from Tom Vanderbilt over at Nautilus, and the whole thing is worth a read. Oh, and there’s also an app for that.

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Apologies for the silence here lately. I have been working on a couple of longer-than-average posts, as well as some fun projects that I will hopefully be able to share with you here soon. Part of the influence in those upcoming posts is from podcasts I have enjoyed. (Readers of the tipping post may have noticed that two of the main references there were to podcasts as well.)

Thus, I thought readers of this blog might enjoy some of my favorites. There are likely some that I have omitted because I listened to all of their episodes some time ago. Below are those that have stood the test of time or that I am listening to currently.

Economics/Social Science

Analysis: Half-hour episodes on current events with a social scientific perspective.

Data Stories: As you might expect, an audio podcast about data visualization has some weak points. However, this is useful as a who’s-who of the visualization community.

Econtalk: My absolute favorite podcast. Each week, Russ Roberts and a guest discuss research or current events using economics as a lens on the world. Sometimes I think Russ is too hard on statistical methods, but every episode is worth a listen.

Great Economists: Originally a MOOC from MRUniversity, the audio from this course is now available as a condensed series of podcasts.

History of Rome: History’s greatest empire in 170-odd episodes. Although new episodes are no longer being produced, host Mike Duncan has a new project in the pipeline that is expected in September.

Loopcast: DC WarKids and their guests discuss national security and international relations.

More or Less: Tim Harford takes quantitative headlines and questions them, often finding more than meets the eye.

Planet Money: My second-favorite podcast, after Econtalk. The hosts explain current events or applied economics lessons in accessible language with fun examples. A podcast like this focused on politics would immediately become my all-time favorite.

Pop-Up Ideas: Another Tim Harford podcast, this one covers big ideas in social science in a short and punchy manner.

Technology

Accidental Tech Podcast: Marco Arment, Casey Liss, and John Siracusa discuss Apple and web technology. This podcast originated as outtakes of their casual car show, Neutral. A very enjoyable listen every week.

Bitsplitting: Daniel Jalkut interviews technology professionals, many of them entrepreneurs.

Association between tipping and corruption at the country level, by Magnus Torfason. I have no idea what’s going on to the left of zero.

The topic of tipping has been on my mind since a dinner in San Francisco this April, when Allan Dafoe brought up the difference between Sweden and the US. In Europe, the pattern seems to be that workers are paid more and tips are not expected. Sometimes (eg in Germany) a waiter would likely be told to keep the change from a cash payment, but the reason given for this is that making change is demeaning. In the US, most waitstaff are paid a paltry $2.13/hour and make the rest up in tips. Why has the micro-institution of tipping endured in the US, and what are advantages and weaknesses of it?

One advantage of tipping is that it helps solve the principal-agent problem between the restaurateur and the staff. It is difficult for the restaurant manager to monitor the quality of servers, but much easier for the customers to do so. Thus, having customers set the compensation level for servers encourages them to be responsive. This in turn keeps customers coming back to the restaurant, which is the manager’s goal. However, tip-pooling can undermine this effect, as can the opportunity for servers to offer lower quality service to a higher volume of tables.

A major disadvantage to tipping is that it seems only weakly correlated with service quality. In an informal, small-n poll of fellow grad students on the same San Francisco trip, most of us tip a relatively fixed percentage of the bill (20-25 percent) regardless of service. This tends to be associated with work experience in the service industry, which can also lead to higher tipping percentages. Furthermore, small “nudges” such as paying on an iPad that offers tips in round dollar amounts rather than percentages can have a strong effect on the tips received by staff.

Another problem with tipping is uncertainty about when it is or is not appropriate. In a country where it is never appropriate, there is no uncertainty. When tipping exists in some settings but not others, there can be a great deal of uncertainty about when to use it. Restaurants and taxis seem like obvious tipping situations. But what about when you order food for carry-out? (I vote yes, but a smaller percentage.) And why not tip the attendants on a flight, who provide beverage and sometimes food service?

These and other problems with tipping are well-known, yet the micro-institution seems fairly ingrained in American society. If there were one profession where I would add tipping it would be my pharmacist–they often provide fast and friendly service for something I could not do myself. On the whole, though, we would be better off without this confusing and inefficient practice.

In his book Thinking Fast and Slow, Daniel Kahneman describes the brain as made up of two systems. System 1 is fast, emotional, and almost automatic–I think of this as “intuition.” System 2 controls more logical, deliberate processes. There are many factors that can influence which system you use to make a decision (anchoring, availability, substitution, loss aversion, framing, etc.) and Kahneman’s book discusses these. But other environmental factors can influence which system takes over. This post discusses how hunger shifts the balance from System 2 to System 1.

Are judicial rulings based solely on laws and facts? Legal formalism holds that judges apply legal reasons to the facts of a case in a rational, mechanical, and deliberative manner. In contrast, legal realists argue that the rational application of legal reasons does not sufficiently explain the decisions of judges and that psychological, political, and social factors influence judicial rulings. We test the common caricature of realism that justice is “what the judge ate for breakfast” in sequential parole decisions made by experienced judges. We record the judges’ two daily food breaks, which result in segmenting the deliberations of the day into three distinct “decision sessions.” We find that the percentage of favorable rulings drops gradually from ≈65% to nearly zero within each decision session and returns abruptly to ≈65% after a break. Our findings suggest that judicial rulings can be swayed by extraneous variables that should have no bearing on legal decisions.

The Economistsummarized the paper and produced a graphic with the main takeaway:

The results show that the innate flight response to carbon dioxide in fruit flies is controlled by two parallel neural circuits, depending on how satiated the animals are. “If the fly is hungry, it will no longer rely on the ‘direct line’ but will use brain centres to gauge internal and external signals and reach a balanced decision,” explains Grunwald-Kadow. “It is fascinating to see the extent to which metabolic processes and hunger affect the processing systems in the brain,” she adds.

Remember this next time you’re trying to decide between working through lunch or grabbing a bite to eat. Do your body and your neighbors a favor by taking a break.